ArticleAnimal genetics2019
Accuracies of genomic prediction for twenty economically important traits in Chinese Simmental beef cattle.
Article in Animal genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 34 citations in OpenAlex.
- Estimation of genomically enhanced breeding values, and their validation accuracies in the Afrikaner and Brahman beef cattle breeds of South Africa.Tropical animal health and production · 2025Article
- Comprehensive Multi-omics Analysis of Regulatory Variants for Body Weight in Cattle.Genomics, proteomics & bioinformatics · 2025Article
- Enhanced genetic fine mapping accuracy with Bayesian Linear Regression models in diverse genetic architectures.PLoS genetics · 2025Article
- Genomic prediction and genetic parameter estimation for unsaturated and saturated fatty acids in Canadian dairy cattle.Scientific reports · 2025Article
- Effects of Different Generations and Sex on Physiological, Biochemical, and Growth Parameters of Crossbred Beef Cattle byAnimals : an open access journal from MDPI · 2023Article
- Article
- Selective genotyping to implement genomic selection in beef cattle breeding.Frontiers in genetics · 2023Article
- Incorporating kernelized multi-omics data improves the accuracy of genomic prediction.Journal of animal science and biotechnology · 2022Article
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- Exploring the size of reference population for expected accuracy of genomic prediction using simulated and real data in Japanese Black cattle.BMC genomics · 2021Article
- Estimation of Genetic Correlations of Primal Cut Yields with Carcass Traits in Hanwoo Beef Cattle.Animals : an open access journal from MDPI · 2021Article
- An evaluation of the predictive performance and mapping power of the BayesR model for genomic prediction.G3 (Bethesda, Md.) · 2021Article
- Validation of the Prediction Accuracy for 13 Traits in Chinese Simmental Beef Cattle Using a Preselected Low-Density SNP Panel.Animals : an open access journal from MDPI · 2021Article
- Genomic prediction for growth using a low-density SNP panel in dromedary camels.Scientific reports · 2021Article
- Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle.Animals : an open access journal from MDPI · 2021Article
- Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle.Frontiers in genetics · 2021Article
- Accuracies of Genomic Prediction for Growth Traits at Weaning and Yearling Ages in Yak.Animals : an open access journal from MDPI · 2020Article
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
Abstract
Genomic prediction has been widely utilized to estimate genomic breeding values (GEBVs) in farm animals. In this study, we conducted genomic prediction for 20 economically important traits including growth, carcass and meat quality traits in Chinese Simmental beef cattle. Five approaches (GBLUP, BayesA, BayesB, BayesCπ and BayesR) were used to estimate the genomic breeding values. The predictive accuracies ranged from 0.159 (lean meat percentage estimated by BayesCπ) to 0.518 (striploin weight estimated by BayesR). Moreover, we found that the average predictive accuracies across 20 traits were 0.361, 0.361, 0.367, 0.367 and 0.378, and the averaged regression coefficients were 0.89, 0.86, 0.89, 0.94 and 0.95 for GBLUP, BayesA, BayesB, BayesCπ and BayesR respectively. The genomic prediction accuracies were mostly moderate and high for growth and carcass traits, whereas meat quality traits showed relatively low accuracies. We concluded that Bayesian regression approaches, especially for BayesR and BayesCπ, were slightly superior to GBLUP for most traits. Increasing with the sizes of reference population, these two approaches are feasible for future application of genomic selection in Chinese beef cattle.
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